Utilities

change Change

Changes a model Parameter to some value during an analysis.

Syntax:

change(change_dict=none, relative=false, name='change', **kwargs)

Required:

\**kwargs: Alternative method to specify parameter:value pairs to change

Optional:

change_dict: Dictionary of parameter:value pairs to change.

relative: Whether to increment from the parameters current value or not

name: Name of action

dc_fields DCFields

An action that saves the DC (carrier) fields at all nodes, frequencies, and higher order modes for the current state of the simulation.

Syntax:

dc_fields(name='dcfields')

Optional:

name: Name of the solution generated by this action

debug Debug

An action that will start an IPython debug shell.

To access the current model use state.model.

Syntax:

debug(name='Debug')

maximize Maximize

An action that maximizes some detector output by applying some feedback to multiple targets in a model. Extra keyword arguments are passed on to the Scipy method:

minimize This action offers a simplified interface that allows an optimization to be done during a simulation. By default the the Nelder-Mead optimization method is used but can be overridden. The user should read the Scipy documentation to determine which options should be used which are method dependant.

Syntax:

maximize(detector, parameter, *args, name='maximize', **kwargs)

Required:

detector: The name of the detector output to maximize / minimize.

parameter: The parameter or name of the parameter to optimize, or a tuple of parameters when using multiple targets to optimize over.

kwargs: Optional parameters passed to the Scipy optimisation routine as the options input. See Scipy method documentation to determine what is available.

Optional:

bounds: A pair of (lower, upper) bounds on the parameter value. Requires a method that uses bounds.

offset: An offset applied to the detector output when optimizing, defaults to 0.

kind: Either ‘max’ for maximization or ‘min’ for minimization, defaults to ‘max’.

max_iterations: Maximum number of solver iterations, defaults to 10000.

method: Optimisation method to use, see Scipy documentation for options.

name: The name of this action, defaults to ‘maximize’.

update_maps: If you are changing some parameter or variable that a Map depends on then setting this flag to True will recompute the Map data for each iteration of the optimiser.

pre_step: Action to run on each step of the optimisation.

See Also:: minimize

minimize Minimize

An action that minimizes some detector output by applying some feedback to multiple targets in a model. Extra keyword arguments are passed on to the Scipy method:

minimize This action offers a simplified interface that allows an optimization to be done during a simulation. By default the the Nelder-Mead optimization method is used but can be overridden. The user should read the Scipy documentation to determine which options should be used which are method dependant.

Syntax:

minimize(detector, parameter, *args, name='minimize', **kwargs)

Required:

detector: The name of the detector output to maximize / minimize.

parameter: The parameter or name of the parameter to optimize, or a tuple of parameters when using multiple targets to optimize over.

kwargs: Optional parameters passed to the Scipy optimisation routine as the options input. See Scipy method documentation to determine what is available.

Optional:

bounds: A pair of (lower, upper) bounds on the parameter value. Requires a method that uses bounds.

offset: An offset applied to the detector output when optimizing, defaults to 0.

kind: Either ‘max’ for maximization or ‘min’ for minimization, defaults to ‘max’.

max_iterations: Maximum number of solver iterations, defaults to 10000.

method: Optimisation method to use, see Scipy documentation for options.

name: The name of this action, defaults to ‘maximize’.

update_maps: If you are changing some parameter or variable that a Map depends on then setting this flag to True will recompute the Map data for each iteration of the optimiser.

pre_step: Action to run on each step of the optimisation.

See Also:: maximize

noise_projection NoiseProjection

Syntax:

noise_projection(f, *output_nodes, scaling=none, name='loop')

plot Plot

Syntax:

plot(name=abcd)

print Printer

Syntax:

print(*args, name='printer', eval=true)

print_model PrintModel

An action that prints the model object being currently used to run actions.

Syntax:

print_model(name='print_model')

print_model_attr PrintModelAttr

Prints an attribute of the model being currently used.

Syntax:

print_model_attr(*args, eval=true, prefix='')

Required:

\*args: Strings input for the attribute to print

Optional:

eval: When True symbolic expressions will be evaluated before printing. Defaults to True.

prefix: Optional string to print before the attributes

save_matrix SaveMatrix

An action that will save the current state of the matrix being used by the simulation.

Not something that should be used lightly in loops or multiple times in a large simulation. Using this in something like a full LIGO model with many HOMs and sidebands will quickly fill up memory.

Syntax:

save_matrix(name='savematrix')